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.gitattributes

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 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
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+kddcup.data filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+language:
+- en
+tags:
+- kddcup
+- tabular_classification
+- binary_classification
+pretty_name: Kddcup
+task_categories:  # Full list at https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts
+- tabular-classification
+configs:
+- kddcup
+---
+# Kddcup
+The Kddcup dataset.
+
+# Configurations and tasks
+| **Configuration**     | **Task**                  |
+|-----------------------|---------------------------|
+| kddcup                | Multiclass classification.|

kddcup.data

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3ec2301a9a5d81b40937ba155b4713a77b60e85b89f0423257e58d566aa979fb
+size 742579829

kddcup.py

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+"""Kddcup Dataset"""
+
+from typing import List
+from functools import partial
+
+import datasets
+
+import pandas
+
+
+VERSION = datasets.Version("1.0.0")
+
+_ENCODING_DICS = {
+	"class": {value: i
+			  for value, i in enumerate("normal.",
+										"buffer_overflow.",
+										"loadmodule.",
+										"perl.",
+										"neptune.",
+										"smurf.",
+										"guess_passwd.",
+										"pod.",
+										"teardrop.",
+										"portsweep.",
+										"ipsweep.",
+										"land.",
+										"ftp_write.",
+										"back.",
+										"imap.",
+										"satan.",
+										"phf.",
+										"nmap.",
+										"multihop.",
+										"warezmaster.",
+										"warezclient.",
+										"spy.",
+										"rootkit.")
+	}
+}
+
+DESCRIPTION = "Kddcup dataset."
+_HOMEPAGE = ""
+_URLS = ("")
+_CITATION = """"""
+
+# Dataset info
+urls_per_split = {
+	"train": "https://huggingface.co/datasets/mstz/kddcup/resolve/main/kddcup.data"
+}
+features_types_per_config = {
+	"kddcup": {
+		"duration": datasets.Value("float"),
+		"protocol_type": datasets.Value("string"),
+		"service": datasets.Value("string"),
+		"flag": datasets.Value("string"),
+		"src_bytes": datasets.Value("integer"),
+		"dst_bytes": datasets.Value("integer"),
+		"land": datasets.Value("integer"),
+		"wrong_fragment": datasets.Value("integer"),
+		"urgent": datasets.Value("integer"),
+		"hot": datasets.Value("integer"),
+		"num_failed_logins": datasets.Value("integer"),
+		"logged_in": datasets.Value("integer"),
+		"num_compromised": datasets.Value("integer"),
+		"root_shell": datasets.Value("integer"),
+		"su_attempted": datasets.Value("integer"),
+		"num_root": datasets.Value("integer"),
+		"num_file_creations": datasets.Value("integer"),
+		"num_shells": datasets.Value("integer"),
+		"num_access_files": datasets.Value("integer"),
+		"num_outbound_cmds": datasets.Value("integer"),
+		"is_host_login": datasets.Value("integer"),
+		"is_guest_login": datasets.Value("integer"),
+		"count": datasets.Value("integer"),
+		"srv_count": datasets.Value("integer"),
+		"serror_rate": datasets.Value("float"),
+		"srv_serror_rate": datasets.Value("float"),
+		"rerror_rate": datasets.Value("float"),
+		"srv_rerror_rate": datasets.Value("float"),
+		"same_srv_rate": datasets.Value("float"),
+		"diff_srv_rate": datasets.Value("float"),
+		"srv_diff_host_rate": datasets.Value("float"),
+		"dst_host_count": datasets.Value("integer"),
+		"dst_host_srv_count": datasets.Value("integer"),
+		"dst_host_same_srv_rate": datasets.Value("float"),
+		"dst_host_diff_srv_rate": datasets.Value("float"),
+		"dst_host_same_src_port_rate": datasets.Value("float"),
+		"dst_host_srv_diff_host_rate": datasets.Value("float"),
+		"dst_host_serror_rate": datasets.Value("float"),
+		"dst_host_srv_serror_rate": datasets.Value("float"),
+		"dst_host_rerror_rate": datasets.Value("float"),
+		"dst_host_srv_rerror_rate": datasets.Value("float"),
+		"class": datasets.ClassLabel(num_classes=23,
+									 names=("normal.", "buffer_overflow.", "loadmodule.", "perl.", "neptune.",
+									 		"smurf.", "guess_passwd.", "pod.", "teardrop.", "portsweep.",
+											"ipsweep.", "land.", "ftp_write.", "back.", "imap.", "satan.",
+											"phf.", "nmap.", "multihop.", "warezmaster.", "warezclient.",
+											"spy.", "rootkit.")),
+	}
+}
+features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}
+
+
+class KddcupConfig(datasets.BuilderConfig):
+	def __init__(self, **kwargs):
+		super(KddcupConfig, self).__init__(version=VERSION, **kwargs)
+		self.features = features_per_config[kwargs["name"]]
+
+
+class Kddcup(datasets.GeneratorBasedBuilder):
+	# dataset versions
+	DEFAULT_CONFIG = "kddcup"
+	BUILDER_CONFIGS = [
+		KddcupConfig(name="kddcup", description="Kddcup for multiclass classification.")		
+	]
+
+
+	def _info(self):
+		info = datasets.DatasetInfo(description=DESCRIPTION, citation=_CITATION, homepage=_HOMEPAGE,
+									features=features_per_config[self.config.name])
+
+		return info
+	
+	def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+		downloads = dl_manager.download_and_extract(urls_per_split)
+
+		return [
+			datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloads["train"]}),
+		]
+	
+	def _generate_examples(self, filepath: str):
+		data = pandas.read_csv(filepath, header=None)
+		data = self.preprocess(data)
+
+		for row_id, row in data.iterrows():
+			data_row = dict(row)
+
+			yield row_id, data_row
+
+	def preprocess(self, data: pandas.DataFrame) -> pandas.DataFrame:
+		data.columns = [f"feature_{i}" for i in range(5000)] + ["class"]
+		for feature in _ENCODING_DICS:
+			encoding_function = partial(self.encode, feature)
+			data.loc[:, feature] = data[feature].apply(encoding_function)
+				
+		return data[list(features_types_per_config[self.config.name].keys())]
+
+	def encode(self, feature, value):
+		if feature in _ENCODING_DICS:
+			return _ENCODING_DICS[feature][value]
+		raise ValueError(f"Unknown feature: {feature}")